Apparatus and method for encoding video

ABSTRACT

A video encoding apparatus includes at least one processor. The at least one processor is configured to adjust a size of a first quantization parameter with reference to a characteristic of quantization coefficients generated from input data by using the first quantization parameter, to determine the first quantization parameter of the adjusted size as a final quantization parameter, and to quantize the input data by using the final quantization parameter to generate output data.

CROSS-REFERENCE TO RELATED APPLICATIONS

This U.S. non-provisional patent application claims priority under 35U.S.C. § 119 to Korean Patent Application No. 10-2017-0154286, filed onNov. 17, 2017 in the Korean Intellectual Property Office, thedisclosures of which are incorporated by reference herein in theirentireties.

BACKGROUND 1. Field

Embodiments of the present disclosure relate to a method and anapparatus for processing an image. More particularly, embodiments of thepresent disclosure relate to a method and an apparatus for encoding avideo.

2. Description of Related Art

Video encoding may refer to the process of generating encoded datahaving a smaller capacity than original data from image data or videodata composed of a series of image data. Decoded data that are generatedby decoding the encoded data or a bitstream may be the same as ordifferent from original data depending on a video encoding manner. Forexample, data that are decoded from data encoded according to losslesscompression may be the same as original data, but data that are decodedfrom data encoded according to lossy compression may be different fromoriginal data.

One of the principal problems associated with video encoding is theproblem of reducing a difference between decoded data and original datawhile reducing the size of data encoded according to the lossycompression, that is, a bitrate of the bitstream.

SUMMARY

Embodiments of the present disclosure provide a method and an apparatusfor selecting a quantization parameter efficiently.

The technical problem to be solved by embodiments of the presentdisclosure is not limited to the above-described technical problems, andother technical problems can be deduced from the following embodiments.

According to an exemplary embodiment, a video encoding apparatus mayinclude at least one processor. The at least one processor may beconfigured to adjust a size of a first quantization parameter withreference to (based on) a characteristic of quantization coefficientsgenerated from input data by using the first quantization parameter, todetermine the first quantization parameter of the adjusted size as afinal quantization parameter, and to quantize the input data by usingthe final quantization parameter to generate output data.

According to an exemplary embodiment, a video encoding method which isperformed by at least one processor may include performing quantizationon input data by using a first quantization parameter to generatequantization coefficients, adjusting a size of the first quantizationparameter with reference to (based on) a characteristic of thequantization coefficients generated by using the first quantizationparameter, determining the first quantization parameter of the adjustedsize as a final quantization parameter, and quantizing the input data byusing the final quantization parameter to generate output data.

According to an exemplary embodiment, a video encoding method which isperformed by at least one processor may include determining at least onetransformation unit associated with a coding unit, performing frequencytransformation on pieces of residual data included in the at least onetransformation unit to generate transformed coefficients associated withthe at least one transformation unit, performing quantization on thetransformed coefficients by using a first quantization parameter togenerate quantization coefficients, adjusting a size of the firstquantization parameter with reference to (based on) a characteristic ofthe quantization coefficients generated by using the first quantizationparameter, to determine a final quantization parameter, and quantizingthe transformed coefficients by using the determined final quantizationparameter.

BRIEF DESCRIPTION OF THE FIGURES

The above and other objects and features of the inventive conceptsdescribed herein will become apparent by describing in detail exemplaryembodiments thereof with reference to the accompanying drawings.

FIG. 1 illustrates a block diagram of a video encoding apparatus,according to an embodiment.

FIG. 2A illustrates a video encoding apparatus, according to anembodiment.

FIG. 2B is a flowchart illustrating a video encoding method performed inthe video encoding apparatus of FIG. 2A, according to an embodiment.

FIG. 3 is a conceptual diagram illustrating an operation of adjusting aninitial quantization parameter with reference to (based on) acharacteristic of quantization coefficients generated by using theinitial quantization parameter, according to an embodiment.

FIG. 4A illustrates a progression for describing the case whererestoration data to be generated by using an initial quantizationparameter and restoration data to be generated by using anotherquantization parameter are fully the same as each other, according to anembodiment. In the embodiment of FIG. 4A, the size of the otherquantization parameter is greater than that of the initial quantizationparameter.

FIG. 4B illustrates a progression for describing the case whererestoration data to be generated by using an initial quantizationparameter and restoration data to be generated by using anotherquantization parameter are different from each other, according to anembodiment. In the embodiment of FIG. 4B, the size of the otherquantization parameter is greater than that of the initial quantizationparameter within a reference range.

FIG. 5 is a flowchart illustrating a method for deciding a finalquantization parameter with reference to (based on) quantizationcoefficients generated by using an initial quantization parameter,according to an embodiment.

FIG. 6 illustrates a decision model for outputting a final quantizationparameter based on a characteristic of quantization coefficientsgenerated by using an initial quantization parameter, according to anembodiment.

FIG. 7 illustrates a coding unit/partition for each depth according toan embodiment.

FIG. 8 illustrates a relationship between a coding unit and atransformation unit, according to an embodiment.

FIG. 9 illustrates a block diagram of another video encoding apparatus,according to an embodiment.

FIG. 10 is a flowchart illustrating a method in which the video encodingapparatus encodes an image.

FIG. 11 illustrates a block diagram of another video decoding apparatus,according to an embodiment.

FIG. 12 is a flowchart illustrating a method in which the video decodingapparatus decodes an image.

FIG. 13 illustrates a block diagram of an exemplary configuration of anelectronic system that performs a video encoding method and a videodecoding method, according to an embodiment.

DETAILED DESCRIPTION

Below, embodiments of the present disclosure will be described in detailand clearly to such an extent that those (hereinafter referred to as“ordinary those”) skilled in the art easily implement the inventiveconcepts described herein.

Below, the terms “unit” or “module” used in the specification may mean ahardware component or an electronic circuit such as a field programmablegate array (FPGA) or an application specific integrated circuit (ASIC).Such terms may also refer to a combination of software instructionsexecuted by a hardware component or electronic circuit, as well as thehardware component or electronic circuit and/or a memory that stores thesoftware instructions.

FIG. 1 illustrates a block diagram of a video encoding apparatus,according to an embodiment.

A video encoding apparatus 10 may be one of various apparatuses thatprocess video data (or image data). According to an embodiment, thevideo encoding apparatus 10 may be of a type that includes a display tooutput video data. For example, the video encoding apparatus 10 may be amobile phone, a desktop personal computer (PC), a laptop PC, a tabletPC, or the like. The video encoding apparatus 10 may also be of a typethat includes a camera module to generate video data, such as a digitalcamera, a digital camcorder, a smartphone, or the like. Also, the videoencoding apparatus 10 may be a server that performs video encoding forthe purpose of transmitting data through a communication channel such asa network. Also, the video encoding apparatus 10 may be implemented withone or more semiconductor chips as a part included in theabove-described apparatuses, and may include a computer-readable storagemedium which stores software implemented with instructions executable bya processor, a central processing unit (CPU), a graphic processing unit(GPU), or the like for the purpose of performing video encoding isstored.

The video encoding apparatus 10 may include at least one processor.Modules illustrated in FIG. 1 may be implemented by one processor, andmay be independently implemented with different processors, and may alsobe a combination of such processors and software executed by theprocessors, as well as memory that stores the software executed by theprocessors.

The video encoding apparatus 10 may generate encoded data (e.g., anencoded bitstream) by encoding original video data 5. A quantizationparameter decision module 320 of a quantization module 300 may generatea quantization parameter QP corresponding to a block. For example, thequantization parameter QP may be generated to have different values fordifferent respective blocks. The video encoding apparatus 10 accordingto an embodiment may include a control module 100, a transformationmodule 200, the quantization module 300, a de-quantization module 400,an inverse transformation module 500, a deblocking/SAO filter module 600(sample adaptive offset filter module), a decoded frame buffer 700, anintra prediction module 800, and inter prediction module 900, and mayinclude operation blocks to operate addition or subtraction of data.

The control module 100 may control video encoding. For example, thecontrol module 100 may receive the original video data 5, and may send acontrol signal to other modules included in the video encoding apparatus10 as illustrated by a dotted line.

The transformation module 200 may generate input data D_IN bytransforming residual data D_RES. Residual data D_Res is datarepresenting a difference between original data D_ORG and predictiondata D_PRE. For example, the transformation module 200 may generate theinput data D_IN by performing discrete cosine transform (DCT) on theresidual data D_RES. Thus, the residual data D_RES of a spatial domainmay be transformed to the input data D_IN of a frequency domain.

The quantization module 300 (or a quantizer) may obtain output dataD_OUT by quantizing the input data D_IN. For example, the quantizationmodule 300 may quantize the input data D_IN depending on thequantization parameter QP. As will be described later, the quantizationmodule 300 may generate a quantization parameter adjusted to improve avideo quality of encoded data generated from the output data D_OUT. Thatis, the quantization module 300 may generate an adjusted quantizationparameter adjusted to improve a video quality of data decoded from abitstream, and may obtain the output data D_OUT by quantizing the inputdata D_IN depending on the adjusted quantization parameter. Asillustrated in FIG. 1, the quantization module 300 may include thequantization parameter decision module 320 and a quantization processor340.

The quantization parameter decision module 320 may decide a quantizationparameter based on a characteristic of quantized coefficients. Forexample, the quantization parameter decision module 320 may quantize theinput data D_IN of a frequency domain by using a given initialquantization parameter to generate the quantization coefficients and mayincrease or decrease the initial quantization parameter with referenceto a characteristic of the generated quantization coefficients. That is,the initial quantization parameter may be increased or decreased basedon a characteristic of the generated quantization coefficients, suchthat the increase or decrease would not occur or would be by a differentamount or degree if the characteristic were different.

The quantization processor 340 may obtain the output data D_OUT byquantizing the input data D_IN depending on a quantization parameter.

The de-quantization module 400 and the inverse transformation module 500may perform operations that are inverse to/of the quantization module300 and the transformation module 200. For example, the de-quantizationmodule 400 may de-quantize the output data D_OUT, and the inversetransformation module 500 may generate data of a spatial domain byinversely transforming data generated by the de-quantization module 400,that is, data of a frequency domain. The data generated by the inversetransformation module 500 may be decoded residual data.

The deblocking/SAO filter module 600 and the decoded frame buffer 700may generate and store decoded frame data for inter prediction. Thedeblocking/SAO filter module 600 may filter data corresponding to a sumof the prediction data D_PRE and residual data de-quantized by thede-quantization module 400 and then inversely transformed by the inversetransformation module 500. Thus, errors due to blocks constituting oneframe may decrease. This may mean that frame data indicating an image ofa better quality are generated. The decoded frame buffer 700 may storeframe data generated by the deblocking/SAO filter module 600 and mayprovide the stored frame data to the inter prediction module 900.

The intra prediction module 800 may generate intra prediction data basedon data, which correspond to a sum of the prediction data D_PRE andresidual data decoded by the de-quantization module 400 and theninversely transformed by the inverse transformation module 500, and theoriginal data D_ORG. For example, the intra prediction module 800 maygenerate intra prediction data by performing intra-frame estimation andintra-frame prediction.

The inter prediction module 900 may generate inter prediction data basedon frame data provided from the decoded frame buffer 700 and theoriginal data D_ORG. For example, the inter prediction module 900 maygenerate inter prediction data by performing motion estimation andmotion compensation.

One of the intra prediction data and inter prediction data may beselected by the control module 100 as the prediction data D_PRE and maybe used to generate the residual data D_RES from the original dataD_ORG.

In FIG. 1, the original data D_ORG may be image data included in one ofmultiple blocks constituting one frame of the original video data 5. Forexample, the original video data 5 including multiple frames may beencoded for each of multiple blocks of each of multiple frames. Thus,the original data D_ORG, the prediction data D_PRE, the residual dataD_RES, the input data D_IN, and the output data D_OUT may correspond toone block. The quantization parameter decision module 320 of thequantization module 300 may decide a quantization parametercorresponding to a block. For example, the quantization parameter may bedetermined to have different values for different respective blocks.

FIG. 2A indicates a video encoding apparatus, according to anembodiment.

A video encoding apparatus 2000 may encode video data and may output anencoded bitstream. The video encoding apparatus 2000 according to anembodiment may include all or a part (e.g., the quantization module 300of FIG. 1) of the video encoding apparatus 10 of FIG. 1. Accordingly,the video encoding apparatus 2000 may perform all or a part of theoperations of the video encoding apparatus 10 described with referenceto FIG. 1.

The video encoding apparatus 2000 may include at least one processor2300. An operation of the video encoding apparatus 2000 to be describedbelow may be performed by the at least one processor 2300.

Input data 2100 may include transformation coefficients that aregenerated by performing frequency transformation on residual datagenerated with respect to original data, but is not limited thereto.

The video encoding apparatus 2000 may perform quantization on the inputdata 2100 by using an initial quantization parameter (QP0) 2050 and maygenerate quantization coefficients 2500.

The initial quantization parameter 2050 according to an embodiment maybe a quantization parameter that is determined in advance depending onthe input data 2100. For example, the initial quantization parameter2050 may be a value that is basically determined for each coding unit orfor each transformation unit. The video encoding apparatus 2000according to an embodiment may decide the initial quantization parameter2050 based on a bitrate of a bitstream generated by encoding originalvideo data. In the case where a sufficient margin is present in abitrate, the initial quantization parameter 2050 may be determined to berelatively small; if not, the initial quantization parameter 2050 may bedetermined to be relatively great. According to an embodiment,information about the initial quantization parameter 2050 may be encodedand transmitted to a video decoding apparatus in the form of abitstream.

The video encoding apparatus 2000 may adjust the size of the initialquantization parameter 2050 with reference to (based on) thequantization coefficients 2500. The initial quantization parameter ofthe adjusted size may also be determined as a final quantizationparameter (QP1) 2700 to be used for quantization of the input data 2100.The video encoding apparatus 2000 may quantize the input data 2100 byusing the final quantization parameter 2700 and may obtain output data2900. Below, an operation of the video encoding apparatus 2000 will bemore fully described with reference to FIG. 2B.

FIG. 2B is a flowchart illustrating a video encoding method performed ina video encoding apparatus, according to an embodiment.

In operation S2200, the video encoding apparatus 2000 may performquantization on input data by using an initial quantization parameterand may generate quantization coefficients. Below, it is assumed thatthe initial quantization parameter has a value of 22.

Referring to FIG. 3, a transformed coefficient 3200 and a transformedcoefficient 3600 indicate input data according to an embodiment. Each ofthe transformed coefficient 3200 and the transformed coefficient 3600may be a coefficient that is obtained by performing frequencytransformation on residual data generated with respect to original data.Each of the transformed coefficient 3200 and the transformed coefficient3600 may be composed of 16 coefficients, and the 16 coefficients may beillustrated in the form of a two-dimensional arrangement (e.g., TC(i,j),0<=i<4 and 0<=j<4) or in the form of a one-dimensional arrangement(e.g., TC(k), 0<=k<15). However, the composition and form of thetransformed coefficient 3200 and the transformed coefficient 3600 maynot be limited thereto.

A quantization coefficient 3400 and a quantization coefficient 3800indicate results of quantizing the transformed coefficient 3200 and thetransformed coefficient 3600 by using an initial quantization parameter3300, respectively. Each of the quantization coefficient 3400 and thequantization coefficient 3800 may be composed of 16 coefficients, andthe 16 coefficients may be illustrated in the form of a two-dimensionalarrangement (e.g., QC(i,j), 0<=i<4 and 0<=j<4) or in the form of aone-dimensional arrangement (e.g., QC(k), 0<=k<15). However, thecomposition and form of the quantization coefficient 3400 and thequantization coefficient 3800 may not be limited thereto. Below, acoefficient of a (x,y)-th location may mean a value (i.e., A(x,y)) atthe x-th row and the y-th column in a coefficient A(i,j) (0<=i<4 and0<=j<4).

A quantization step Q_(step) used to perform quantization may beobtained from the quantization parameter QP by using the followingequation.

$\begin{matrix}{Q_{step} \approx 2^{\frac{{Q\; P} - 4}{6}}} & \left\lbrack {{Equation}\mspace{14mu} (1)} \right\rbrack\end{matrix}$

For example, a quantization step corresponding to an initialquantization parameter 3300 may be determined to be “8”, and mayincrease to “16” if the initial quantization parameter increases to“28”. Accordingly, an increase in the size of the quantization parametermay mean an increase in the size of the quantization step. Also,increasing a size of the quantization step two times may mean toincrease the size of an existing quantization parameter to a sizecorresponding to the quantization step which is increased in size twotimes.

The quantization coefficient 3400 and the quantization coefficient 3800may be obtained by quantizing the transformed coefficient 3200 and thetransformed coefficient 3600 by using the following equation,respectively.

Q _(coeff)=lower bound(T _(coeff)+(R _(coeff) ×Q _(step)))/Q _(step))(Q_(coeff): quantization coefficient, T _(coeff): transformed coefficient,R _(coeff): rounding offset for quantization, and Q _(step):quantization step).  [Equation (2)]

In operation S2400, the video encoding apparatus 2000 may adjust thesize of the initial quantization parameter with reference to (based on)a characteristic of the quantization coefficients generated in operationS2200.

Returning to FIG. 3, the video encoding apparatus 2000 may increase theinitial quantization parameter 3300 by 6 with reference to (based on)the quantization coefficient 3400 to decide the final quantizationparameter 3500 (e.g., 28) to be used for quantization of the transformedcoefficient 3200. For example, the video encoding apparatus 2000 mayincrease the initial quantization parameter 3300 by 6 with reference to(based on) the quantization coefficient 3800 to decide a finalquantization parameter 3900 (e.g., 28) to be used for quantization ofthe transformed coefficient 3600.

In operation S2400, the video encoding apparatus 2000 may determinewhether restoration data to be generated by restoring input data byusing the initial quantization parameter and restoration data to begenerated by restoring the input data by using another quantizationparameter are the same as each other or different from each other withina reference range. The size of the other quantization parameter isgreater than that of the initial quantization parameter. The videoencoding apparatus 2000 may in advance determine whether pieces ofrestoration data to be generated by using different quantizationparameters (e.g., an initial quantization parameter and anotherquantization parameter with an adjusted size) are the same as each otheror are different from each other within a reference range. The videoencoding apparatus may determine whether the pieces of restoration datato be generated are the same as each other or different from each otherwith reference to only the quantization parameters generated inoperation S2200 without the process of generating restoration dataactually and comparing the generated restoration data with correspondingdata.

Below, one embodiment will be more fully described with reference toFIG. 4A. Restoration data 4200 may be generated by performing inversequantization on quantization coefficients 4100 that are generated byquantizing a transformed coefficient 4000 by using the initialquantization parameter. Restoration data 4400 may be generated byperforming inverse quantization on quantization coefficient 4300 that isgenerated by quantizing the transformed coefficient 4000 by usinganother quantization parameter (e.g., 28) which is greater in size thanthat of the initial quantization parameter. The restoration data 4200are the same as restoration data 4400.

Accordingly, the video encoding apparatus 2000 may decide anotherquantization parameter with a size greater than that of the initialquantization parameter as a final quantization parameter to be used forquantization of the transformed coefficient 4000, thereby improvingefficiency to encode. That is, since the restoration data 4200 are thesame as restoration data 4400, even though encoding and decoding areperformed by using another quantization parameter with a size greaterthan that of the initial quantization parameter, degradation of an imagemay not occur compared with the case of performing encoding and decodingby using the initial quantization parameter.

Below, another embodiment will be more fully described with reference toFIG. 4B. Restoration data 4700 may be generated by performing inversequantization on quantization coefficients 4600 that are generated byquantizing a transformed coefficient 4500 by using the initialquantization parameter. Restoration data 4900 may be generated byperforming inverse quantization on quantization coefficient 4800 that isgenerated by quantizing the transformed coefficient 4500 by usinganother quantization parameter (e.g., 28) with a size greater than thatof the initial quantization parameter. Since values at a (1, 3) locationare “8” and “0”, the restoration data 4700 and the restoration data 4900are different from each other. However, even in this case, the videoencoding apparatus 2000 may decide another quantization parameter with asize greater than that of the initial quantization parameter, as a finalquantization parameter to be used for quantization of the transformedcoefficient 4500, thereby improving efficiency to encode.

That is, in the case where a difference between the restoration data4700 and the restoration data 4900 is within a reference range eventhough the restoration data 4700 and the restoration data 4900 do notcoincide with each other, the video encoding apparatus 2000 maydetermine that a gain obtained from a decrease in a bitrate provides anadvantage greater than the disadvantage from degradation of an image dueto an increase in using another quantization parameter. According to anembodiment, the case where a difference between the restoration data4700 and the restoration data 4900 is within a reference range mayinclude the case where the number of different coefficients is small ordifferent coefficients indicate a component of a high frequency band.However, cases when differences between restoration data, e.g.,restoration data 4700 and restoration data 4900, is within a referencerange, may not be limited thereto.

According to another embodiment, the video encoding apparatus 2000 mayadjust the size of the initial quantization parameter by using adecision model. Referring to FIG. 6, a decision model 6000 may receivethe quantization coefficients generated in operation S2200 and mayoutput a final quantization parameter in consideration of encodingefficiency and the degree of degradation of an image. The finalquantization parameter may be a value that is obtained by increasing ordecreasing the initial quantization parameter.

The decision model 6000 may be generated based on the machine learning.The machine learning may mean an algorithm technology forclassifying/learning a characteristic of pieces of input data by itself.For example, the machine learning associated with the decision model6000 may be performed by using any one of a principal component analysis(PCA) technique, a deep network learning technique, and a singular valuedecomposition (SVD) technique, using data associated with a lot ofquantization coefficients as an input.

The machine learning associated with the decision model 6000 may beperformed to decide a final quantization parameter for generatingrestoration data of a reference quality or higher corresponding to inputdata, based on information about quantization coefficients. For example,the machine learning associated with the decision model 6000 may includean operation of allowing the decision model 6000 to learn by using thequantization coefficient 3400 of FIG. 3 and the final quantizationparameter 3500 corresponding to the quantization coefficient 3400. Also,the machine learning associated with the decision model 6000 may includean operation of allowing the decision model 6000 to learn by using thetransformed coefficient 3600 of FIG. 3 and the final quantizationparameter 3900 corresponding to the transformed coefficient 3600.

In the above manner, the machine learning associated with the decisionmodel 6000 may be performed by using a myriad of quantizationcoefficients and a final quantization parameter corresponding thereto.As the machine learning is performed, the decision model 6000 may beconsistently updated.

As described above, the video encoding apparatus 2000 may adjust thesize of the initial quantization parameter without actually performingthe process of inverse quantization, with reference to (based on) thequantization coefficients 4100 or only a characteristic associated withthe quantization coefficients 4100. Accordingly, a complicated operation(e.g., calculating rate-distortion costs) performed to decide anotherquantization parameter may be omitted. A determination reference foradjusting the size of the initial quantization parameter, according toan embodiment, will be more fully described with reference to FIG. 5.

In operation S2600, the video encoding apparatus 2000 may decide theinitial quantization parameter of the adjusted size as the finalquantization parameter.

In operation S2800, the video encoding apparatus 2000 may quantize inputdata by using the final quantization parameter determined in operationS2600 and may obtain output data. The video encoding apparatus 2000according to an embodiment may divide each of the quantizationcoefficients generated in operation S2200 by the same value “K” (K beinga positive real number) and may decide the division result values as theoutput data. Here, “K” may be determined differently according to howmuch the initial quantization parameter is adjusted (e.g., an incrementof a quantization step). Referring to FIGS. 4A and 4B, the videoencoding apparatus 2000 may perform only an operation of dividing eachof the quantization coefficients 4100 or the quantization coefficients4600 generated in operation S2200 by “2”, instead of performing anoperation of quantizing the transformed coefficient 4000 or thetransformed coefficient 4500 by using the final quantization parameterdetermined. Accordingly, the video encoding apparatus 2000 may decidethe quantization coefficient 4300 or the quantization coefficient 4800thus obtained as the output data.

FIG. 5 is a flowchart illustrating a method for deciding a finalquantization parameter with reference to (based on) quantizationcoefficients generated by using an initial quantization parameter,according to an embodiment.

Operation S5410, operation S5420, operation S5430, operation S5450,operation S5460, and operation S5480 of FIG. 5 may belong to operationS2400 of FIG. 2B. However, operation S5410, operation S5420, operationS5430, operation S5450, operation S5460, and operation S5480 of FIG. 5may not be essential components of operation S2400 of FIG. 2B. The orderof operation S5410, operation S5420, operation S5430, operation S5450,operation S5460, and operation S5480 of FIG. 5 may be changed. Forexample, one or more of operation S5410, operation S5420, operationS5430, operation S5450, operation S5460, and operation S5480 may beomitted in operation S2400, or any other operation except for operationS5410, operation S5420, operation S5430, operation S5450, operationS5460, and operation S5480 may be added to operation S2400.

In operation S5410, the video encoding apparatus 2000 may performquantization on input data by using an initial quantization parameterand may generate quantization coefficients.

In operation S5420, the video encoding apparatus 2000 may determinewhether all the quantization coefficients generated in operation S5410are an even number. The case where all the quantization coefficients arean even number may mean that another quantization parameter (e.g., aquantization parameter (QP) 28 of FIG. 4A) for compressing input datawithout data loss exists, and the other quantization parameter has agreater value than an initial quantization parameter. If all thequantization coefficients generated in operation S5410 are an evennumber, operation S5430 may be performed; if not, another condition maybe determined in operation S5450.

In operation S5430, the video encoding apparatus 2000 may increase thesize of the initial quantization parameter. For example, if aquantization coefficient with a smallest size among the quantizationcoefficients generated in operation S5410 is 2n (n being a positiveinteger), the video encoding apparatus 2000 may increase a quantizationstep as much as 2^(n) times. Returning to FIG. 3, since all thequantization coefficients 3400 generated by quantizing the transformedcoefficient 3200 by using the initial quantization parameter 3300 are aneven number and a quantization coefficient with the smallest size amongthe quantization coefficients 3400 is “2”, the video encoding apparatus2000 may increase the initial quantization parameter to a value (e.g.,28) corresponding to the size of a quantization step (e.g., 16), whichis two times a size (e.g., 8) of the initial quantization parameter3300.

In operation S5450, the video encoding apparatus 2000 may determinewhether a gain obtained from reduction of the bitrate provides anadvantage that outweighs the disadvantage from degradation of an imagedue to an increase in the initial quantization parameter, based on onlya characteristic of quantization coefficients. Accordingly, the videoencoding apparatus 2000 may determine whether to adjust the size of theinitial quantization parameter, without calculating rate-distortioncosts.

In operation S5420, the video encoding apparatus 2000 may determinewhether the number of quantization coefficients, which are an oddnumber, from among the quantization coefficients generated in operationS5410 is not more than a reference. Returning to FIG. 3, the videoencoding apparatus 2000 may determine whether the number of quantizationcoefficients, which are an odd number, from among 16 quantizationcoefficients generated is not more than 3. A coefficient at (1, 3) amongthe quantization coefficient 3800 generated by quantizing the initialquantization parameter 3300 is an odd number being “1”. This may meanthat loss occurs with regard to the input data (i.e., an image degrades)in the case of quantizing the input data by using another quantizationparameter with a value greater than that of the initial quantizationparameter 3300.

However, as described above, in the case where the number ofquantization coefficients, which are an odd number, from amongquantization coefficients obtained by using an initial quantizationparameter is smaller than a reference, the video encoding apparatus 2000may determine that a gain obtained from reduction of a bitrate providesmore advantage than the disadvantage from degradation of an image due toan increase in the initial quantization parameter is considered.

However, exceptionally, even though the number of quantizationcoefficients, which are an odd number, from among quantizationcoefficients is more than a reference, if most of the odd coefficientsare coefficients indicating a component of a high frequency band, thevideo encoding apparatus 2000 may determine that the degree ofdegradation of an image, which a person feels, is minor. The reason isthat a person is less sensitive to degradation of an image in a highfrequency band than in a low frequency band. Even in this case, thevideo encoding apparatus 2000 may determine that a gain obtained fromreduction of the bitrate provides an advantage that outweighs thedisadvantage from degradation of an image due to an increase in theinitial quantization parameter is considered.

If it is determined that a gain obtained from reduction of the bitrateprovides an advantage that outweighs the disadvantage from degradationof an image due to an increase in the initial quantization parameter,operation S5460 may be performed; if not, operation S5480 may beperformed.

In operation S5460, the video encoding apparatus 2000 may increase thesize of the initial quantization parameter. For example, if aquantization coefficient with the smallest size among the quantizationcoefficients generated in operation S5410 is 2n, the video encodingapparatus 2000 may increase a quantization step as much as 2^(n) times.

Returning to FIG. 3, the quantization coefficient 3800 is composed of 16quantization coefficients generated by quantizing the transformedcoefficient 3600 by using the initial quantization parameter 3300. Only“1” of the 16 quantization coefficients among the quantizationcoefficient 3800 is an odd number. Additionally, the smallest of the 16quantization coefficients among the quantization coefficient 3800 withan even number is “2”. Accordingly, the video encoding apparatus 2000may increase the initial quantization parameter to a value (e.g., 28)corresponding to the size of a quantization step (e.g., 16), which istwo times a size (e.g., 8) of the initial quantization parameter 3300.

In operation S5480, the video encoding apparatus 2000 may increase thesize of the initial quantization parameter by using a decision model.For example, the video encoding apparatus 2000 may output a finalquantization parameter corresponding to the quantization coefficientsgenerated in operation S5410 by using a decision model (e.g., 6000 ofFIG. 6) learned based on a machine learning technique.

FIG. 7 illustrates a coding unit/partition for each depth, according toan embodiment.

The video encoding apparatus 2000 according to an embodiment may use acoding unit based on a layer, for the purpose of performing encoding inconsideration of an image characteristic. The maximum height, themaximum width, and the maximum depth of the coding unit may beadaptively determined according to a characteristic of an image and maybe variously set according to requirement of a user. The size of thecoding unit for each depth may be determined according to the maximumsize of a preset coding unit.

A layer structure 7000 of the coding unit according to an embodimentillustrates the case where the maximum height and the maximum width ofthe coding unit are “64” and the maximum depth is “3”. The maximum depthindicates the total number of times of division from the maximum codingunit to the minimum coding unit. Since a depth becomes deeper along avertical axis of the layer structure 7000 of the coding unit accordingto an embodiment, each of a height and a width of a coding unit for eachdepth is divided. Also, a prediction unit/partition for predictionencoding of a coding unit for each depth is illustrated along ahorizontal axis of the layer structure 7000 of the coding unit.

A coding unit 1310 that is the maximum coding unit of the layerstructure 7000 of the coding unit is “0” in depth and the size of thecoding unit, that is, the height by width is 64×64. A depth becomesdeeper along the vertical axis, and a coding unit 1320 of depth 1, whichis 32×32 in size, a coding unit 1330 of depth 2, which is 16×16 in size,and a coding unit 1340 of depth 3, which is 8×8 in size exist. Thecoding unit 1340 of depth 3, which is 8×8 in size is the minimum codingunit.

Prediction units/partitions of a coding unit are arranged along thehorizontal axis for each depth. If the coding unit 1310 of depth 0,which is 64×64 in size, is a prediction unit, the prediction unit may bepartitioned into a prediction of 64×64 in size included in the codingunit 1310 of 64×64 in size, predictions 1312 of 64×32 in size,predictions 1314 of 32×64 in size, and predictions 1316 of 32×32 insize.

Likewise, if the coding unit 1320 of depth 1, which is 32×32 in size, isa prediction unit, the prediction unit may be partitioned into aprediction of 32×32 in size included in the coding unit 1320 of 32×32 insize, predictions 1322 of 32×16 in size, predictions 1324 of 16×32 insize, and predictions 1326 of 16×16 in size.

Likewise, if the coding unit 1330 of depth 2, which is 16×16 in size, isa prediction unit, the prediction unit may be partitioned into aprediction of 16×16 in size included in the coding unit 1330 of 16×16 insize, predictions 1332 of 16×8 in size, predictions 1334 of 8×16 insize, and predictions 1336 of 8×8 in size.

Likewise, if the coding unit 1340 of depth 3, which is 8×8 in size, is aprediction unit, the prediction unit may be partitioned into aprediction of 8×8 in size included in the coding unit 1340 of 8×8 insize, predictions 1342 of 8×4 in size, predictions 1344 of 4×8 in size,and predictions 1346 of 4×4 in size.

The number of coding units for each depth for including data of the samerange and size increases as a depth becomes deeper. For example, fourcoding units of depth 2 are necessary with regard to data that onecoding unit of depth 1 includes.

FIG. 8 illustrates a relationship between a coding unit and atransformation unit, according to an embodiment.

The video encoding apparatus 2000 according to an embodiment may encodeor decode an image by a coding unit with a size smaller than or the sameas the maximum coding unit, with respect to each of the maximum codingunits. The size of a transformation unit for transformation of anencoding process may be selected based on a data unit, which is notgreater than each coding unit.

For example, when a current coding unit 8000 is 64×64 in size, the videoencoding apparatus 2000 according to an embodiment may performtransformation by using a transformation unit 8200 of 32×32 in size.

Also, the video encoding apparatus 2000 according to an embodiment mayencode data of the coding unit 8000 of 64×64 in size throughtransformation with each of transformation units of 32×32, 16×16, 8×8,and 4×4 in size and may then select a transformation unit in which adifference between original data and the coded data is the smallest.

Residual data that correspond to a difference between original data andprediction data may be included in a transformation unit. The videoencoding apparatus 2000 according to an embodiment may perform frequencytransformation on residual data of the transformation unit to generate atransformed coefficient (e.g., 3200 or 3600 of FIG. 3). Also, the videoencoding apparatus 2000 may quantize a transformed coefficient that isgenerated based on a quantization parameter determined by theabove-described quantization parameter deciding method.

FIG. 9 illustrates a block diagram of another video encoding apparatus,according to an embodiment.

A video encoding apparatus 9000 may include a prediction module 9200, atransformation module 9400, a quantization module 9600, and aquantization parameter decision module 9800. The video encodingapparatus 9000 illustrates an embodiment of the video encoding apparatus10 of FIG. 1. Accordingly, even though omitted below, the abovedescription given with regard to the video encoding apparatus 10 of FIG.1 may be applied to the video encoding apparatus 9000 of FIG. 9. Below,an operation of the video encoding apparatus 9000 will be described withreference to a flowchart of FIG. 10.

FIG. 10 is a flowchart illustrating a method in which a video encodingapparatus encodes an image.

In operation S10100, the prediction module 9200 may perform intraprediction or motion prediction on at least one prediction unit of acurrent coding unit and may generate prediction data for each predictionunit. The prediction data of the prediction unit generated as the motionprediction result may mean residual data between a current predictionunit and a reference prediction unit.

In operation S10200, the transformation module 9400 may decide at leastone transformation unit of a tree structure, on which transformationwill be performed, with respect to the current coding unit including theprediction data generated by the prediction module 9200. Thetransformation module 9400 may perform transformation on at least onetransformation unit included in the current coding unit to generate atransformed coefficient (e.g., 3200 or 3600 of FIG. 3).

In operation S10300, the quantization parameter decision module 9800 maydecide a final quantization parameter by adjusting the size of aninitial quantization parameter with respect to the at least onetransformation unit. In operation S10200, in the case where multipletransformation units associated with the current coding unit aredetermined, the final quantization parameter may be determineddifferently with respect to the multiple transformation units. Forexample, the quantization parameter decision module 9800 may performquantization on a current transformation unit by using the initialquantization parameter and may adjust the size of the initialquantization parameter with reference to (based on) the generated,quantized transformed coefficients. The initial quantization parameterof the adjusted size may be determined as the final quantizationparameter for the current transformation unit. An operation in which thequantization parameter decision module 9800 decides a final quantizationparameter is more fully described with reference to FIGS. 2A to 6.

In operation S10400, the quantization module 9600 may performquantization on the transformed coefficients by using the quantizationparameter determined by the quantization parameter decision module 9800and may generate quantized transformed coefficients.

FIG. 11 illustrates a block diagram of another video decoding apparatus,according to an embodiment.

A video decoding apparatus 11000 may receive a bitstream generated inthe video encoding apparatus 9000 and may decode the received bitstreamto restore an image.

The video decoding apparatus 11000 according to an embodiment mayinclude a quantization parameter decision module 11200, an inversequantization module 11400, an inverse transformation module 11600, and areconstruction module 11800. Below, an operation of the video decodingapparatus 11000 will be described with reference to a flowchart of FIG.12.

FIG. 12 is a flowchart illustrating a method in which a video decodingapparatus decodes an image.

In operation S12100, the quantization parameter decision module 11200may determine at least one transformation unit included in a currentcoding unit.

In operation S12200, the quantization parameter decision module 11200may determine a quantization parameter of the at least onetransformation unit thus determined. In operation S12100, in the casewhere multiple transformation units associated with the current codingunit are determined, the quantization parameter may be determineddifferently with respect to different of the multiple transformationunits, respectively. The quantization parameter decision module 11200according to an embodiment may determine another quantization parameterof the current transformation unit, based on a difference value with aninitial quantization parameter received from a bitstream. According toan embodiment, the initial quantization parameter may be obtained from aheader of a coding unit containing information about a coding unit towhich the current transformation unit belongs.

In operation S12300, the inverse quantization module 11400 may performinverse quantization on the at least one transformation unit by usingthe quantization parameter determined by the quantization parameterdecision module 11200. Transformed coefficients may be restored throughthe inverse quantization, and the restored transformed coefficients maybe referred to as restoration coefficients. First restorationcoefficients may be generated by using a first quantization parameter.Second restoration coefficients may be generated by using a secondquantization parameter, such as the final quantization parameter

In operation S12400, the inverse transformation module 11600 may performinverse transformation on the transformed coefficients restored by theinverse quantization module 11400 to restore residual data included in atransformation unit.

In operation S12500, the reconstruction module 11800 may perform intraprediction or motion compensation on the at least one prediction unit ofthe current coding unit and may restore image data based on the residualdata restored in operation S12400 for each prediction unit.

FIG. 13 illustrates a block diagram of an exemplary configuration of anelectronic system that performs a video encoding method and a videodecoding method, according to an embodiment.

An electronic system 1000 may include a main processor 1101, a workingmemory 1200, a storage device 1300, a communication block 1400, a userinterface 1500, and a bus 1600. For example, the electronic system 1000may be one of electronic devices such as a desktop computer, a laptopcomputer, a tablet computer, a smartphone, a wearable device, a videogame console, a workstation, a server, and an electric vehicle. Theelectronic system 10000 according to an embodiment may include at leastone of the video encoding apparatus described with reference to FIGS. 1to 9 or the video decoding apparatus of FIG. 10. For example, theelectronic system 1000 may include the video encoding apparatus 2000 ofFIG. 2A but is not limited thereto.

The main processor 1101 may control overall operations of the electronicsystem 1000. The main processor 1101 may process various kinds ofarithmetic operations and/or logical operations. To this end, the mainprocessor 1101 may include a special-purpose logic circuit (e.g., afield programmable gate array (FPGA) or application specific integratedchips (ASICs)). For example, the main processor 1101 may include one ormore processor cores and may be implemented with a general-purposeprocessor, a special-purpose processor, or an application processor.

In an embodiment, the main processor 1101 may perform theabove-described video encoding method by executing the instructionsstored in the storage device 1300. For example, the main processor 1101may determine a quantization parameter for input data by using thequantization parameter determining method described with reference toFIG. 5 and may encode the input data by using the determinedquantization parameter.

The main processor 11010 may include a GPU (not illustrated). Forexample, the GPU may execute a program instruction associated withgraphics processing. The GPU may receive graphic data from the outsideand may transmit the graphic data processed by the GPU to the outside.In an embodiment, the GPU may perform the video encoding methoddescribed with reference to FIGS. 1 to 9. For example, the GPU maygenerate a bitstream by encoding original data received from theoutside.

The working memory 1200 may store data to be used in an operation of theelectronic system 1000. For example, the working memory 1200 maytemporarily store data that are processed or will be processed by themain processor 1101. The working memory 1200 may temporarily store avideo bitstream generated by the main processor 1101 or a videobitstream to be processed by the main processor 1101. The working memory1200 may include a volatile memory, such as a dynamic random accessmemory (DRAM), a synchronous DRAM (SDRAM), or the like, and/or anonvolatile memory, such as a phase-change RAM (PRAM), amagneto-resistive RAM (MRAM), a resistive RAM (ReRAM), a ferroelectricRAM (FRAM), or the like.

The storage device 1300 may include at least one memory device and acontroller. The memory device of the storage device 1300 may store dataregardless of power supply. For example, the storage device 1300 mayinclude a nonvolatile memory device such as a flash memory, a PRAM, anMRAM, a ReRAM, a FRAM, or the like. For example, the storage device 1300may include a storage medium such as a solid state drive (SSD), cardstorage, embedded storage, or the like. According to an embodiment, thestorage device 1300 may store a bitstream that is generated by encodingthe above-described original data or video data.

The communication block 1400 may communicate with an externaldevice/system of the electronic system 1000. For example, thecommunication block 1400 may support at least one of various wirelesscommunication protocols such as long term evolution (LTE), worldwideinteroperability for microwave access (WiMax), global system for mobilecommunication (GSM), code division multiple access (CDMA), Bluetooth,near field communication (NFC), wireless fidelity (Wi-Fi), and radiofrequency identification (RFID) and/or at least one of various wiredcommunication protocols such as transfer control protocol/Internetprotocol (TCP/IP), universal serial bus (USB), and Firewire.

The user interface 1500 may perform communication arbitration between auser and the electronic system 1000. For example, the user interface1500 may include input interfaces such as a keyboard, a mouse, a keypad,a button, a touch panel, a touch screen, a touch pad, a touch ball, acamera, a microphone, a gyroscope sensor, and a vibration sensor. Forexample, the user interface 1500 may include output interfaces such as aliquid crystal display (LCD) device, a light emitting diode (LED)display device, an organic LED (OLED) display device, an active matrixOLED (AMOLED) display device, a speaker, and a motor.

The bus 1600 may provide a communication path between the components ofthe electronic system 1000. The components of the electronic system 1000may exchange data with each other based on a bus format of the bus 1600.For example, the bus format may include one or more of various interfaceprotocols such as USB, small computer system interface (SCSI),peripheral component interconnect express (PCIe), mobile PCIe (M-PCIe),advanced technology attachment (ATA), parallel ATA (PATA), serial ATA(SATA), serial attached SCSI (SAS), integrated drive electronics (IDE),enhanced IDE (EIDE), nonvolatile memory express (NVMe), and universalflash storage (UFS).

Meanwhile, the video encoding method and the video decoding method,which are described above, may be implemented with a computer-readablecode in a computer-readable recording medium. The computer-readablerecording medium may include all kinds of storage devices in which dataare stored. Examples of the computer-readable recording medium includeread-only memories (ROMs), random-access memories (RAMs), CD-ROMs,magnetic tapes, floppy disks, optical data storage devices, and carrierwaves (such as data transmission through the Internet). Also, in thecomputer-readable recording medium, a program or codes, which a computercan read out, may be stored and executed in a distributed manner.

The above descriptions are intended to provide exemplary configurationsand operations for implementing the inventive concepts described herein.The scope and spirit of the present disclosure may includeimplementations capable of being obtained by changing or modifyingsimply the above embodiments, in addition to the above-describedembodiments. Also, the scope and spirit of the present disclosure mayinclude implementations capable of being accomplished by changing ormodifying the above-described embodiments afterwards easily.

What is claimed is:
 1. A video encoding apparatus which includes atleast one processor, wherein the at least one processor is configuredto: adjust a size of a first quantization parameter with reference to acharacteristic of quantization coefficients generated from input data byusing the first quantization parameter; determine the first quantizationparameter of the adjusted size as a final quantization parameter; andquantize the input data by using the final quantization parameter togenerate output data.
 2. The video encoding apparatus of claim 1,wherein, if first restoration data to be generated by restoring theinput data by using the first quantization parameter and secondrestoration data to be generated by restoring the input data by using asecond quantization parameter are the same as each other or aredifferent from each other within a reference range is determined withreference to the characteristic of the quantization coefficientsgenerated by using the first quantization parameter, the at least oneprocessor increases the size of the first quantization parameter to asize of the second quantization parameter, and wherein the size of thesecond quantization parameter is greater than the size of the firstquantization parameter.
 3. The video encoding apparatus of claim 2,wherein, if all the quantization coefficients generated by using thefirst quantization parameter are an even number, the at least oneprocessor determines that the first restoration data and the secondrestoration data are the same as each other.
 4. The video encodingapparatus of claim 3, wherein the second quantization parameter is avalue corresponding to a quantization step, a size of which is two timesa size of a quantization step corresponding to the first quantizationparameter.
 5. The video encoding apparatus of claim 2, wherein, if anumber of quantization coefficients, which are an odd number, from amongthe quantization coefficients generated by using the first quantizationparameter is not more than a reference, the at least one processordetermines that the first restoration data and the second restorationdata are different from each other within the reference range.
 6. Thevideo encoding apparatus of claim 2, wherein, if quantizationcoefficients, which are an odd number, from among the quantizationcoefficients generated by using the first quantization parameter arecoefficients indicating a component of a high frequency band, the atleast one processor determines that the first restoration data and thesecond restoration data are different from each other within thereference range.
 7. The video encoding apparatus of claim 1, wherein theat least one processor is further configured to adjust the firstquantization parameter by using a decision model that is generated basedon machine learning, and wherein the decision model receives thequantization coefficients generated by using the first quantizationparameter to output the final quantization parameter.
 8. The videoencoding apparatus of claim 7, wherein the decision model is generatedby using at least one technique of a principal component analysis (PCA)technique, a deep network learning technique, and a singular valuedecomposition (SVD) technique.
 9. A video encoding method which isperformed by at least one processor, the method comprising: performingquantization on input data by using a first quantization parameter togenerate quantization coefficients; adjusting a size of the firstquantization parameter with reference to a characteristic of thequantization coefficients generated by using the first quantizationparameter; determining the first quantization parameter of the adjustedsize as a final quantization parameter; and quantizing the input data byusing the final quantization parameter to generate output data.
 10. Themethod of claim 9, wherein the adjusting of the size of the firstquantization parameter includes: determining whether first restorationdata to be generated by restoring the input data by using the firstquantization parameter and second restoration data to be generated byrestoring the input data by using a second quantization parameter arethe same as each other or are different from each other within areference range, with reference to the characteristic of thequantization coefficients generated by using the first quantizationparameter; and increasing the size of the first quantization parameterto a size of the second quantization parameter if it is determined thatthe first restoration data and the second restoration data are the sameor are different from each other within a reference range, wherein thesize of the second quantization parameter is greater than the size ofthe first quantization parameter.
 11. The method of claim 10, whereinthe determining includes: determining that the first restoration dataand the second restoration data are the same as each other, if all thequantization coefficients generated by using the first quantizationparameter are an even number.
 12. The method of claim 11, wherein thesecond quantization parameter is a value corresponding to a quantizationstep, a size of which is two times a size of a quantization stepcorresponding to the first quantization parameter.
 13. The method ofclaim 10, wherein the determining includes: determining that the firstrestoration data and the second restoration data are different from eachother within the reference range, if a number of quantizationcoefficients, which are an odd number, from among the quantizationcoefficients generated by using the first quantization parameter is notmore than a reference.
 14. The method of claim 10, wherein thedetermining includes: determining that the first restoration data andthe second restoration data are different from each other within thereference range, if quantization coefficients, which are an odd number,from among the quantization coefficients generated by using the firstquantization parameter are coefficients indicating a component of a highfrequency band.
 15. The method of claim 9, wherein the adjusting of thesize of the first quantization parameter includes: adjusting the firstquantization parameter by using a decision model that is generated basedon machine learning.
 16. The method of claim 15, wherein the decisionmodel is generated by using at least one technique of a principalcomponent analysis (PCA) technique, a deep network learning technique,and a singular value decomposition (SVD) technique.
 17. A video encodingmethod which is performed by at least one processor, the methodcomprising: determining at least one transformation unit associated witha coding unit; performing frequency transformation on pieces of residualdata included in the at least one transformation unit to generatetransformed coefficients associated with the at least one transformationunit; performing quantization on the transformed coefficients by using afirst quantization parameter to generate quantization coefficients;adjusting a size of the first quantization parameter with reference to acharacteristic of the quantization coefficients generated by using thefirst quantization parameter, to determine a final quantizationparameter; and quantizing the transformed coefficients by using thedetermined final quantization parameter.
 18. The method of claim 17,wherein the determining of the final quantization parameter includes:determining whether first restoration coefficients to be generated byrestoring the transformed coefficients by using the first quantizationparameter and second restoration coefficients to be generated byrestoring the transformed coefficients by using a second quantizationparameter are the same as each other or are different from each otherwithin a reference range, with reference to the characteristic of thequantization coefficients generated by using the first quantizationparameter; and increasing the size of the first quantization parameterto a size of the second quantization parameter if it is determined thatthe first restoration coefficients and the second restorationcoefficients are the same as each other or are different from each otherwithin the reference range, wherein the size of the second quantizationparameter is greater than the size of the first quantization parameter.19. The method of claim 18, wherein the determining includes:determining that the first restoration coefficients and the secondrestoration coefficients are the same as each other or are differentfrom each other within the reference range, if all the quantizationcoefficients generated by using the first quantization parameter are aneven number or a number of quantization coefficients, which are an oddnumber, from among the quantization coefficients generated by using thefirst quantization parameter is not more than a reference.
 20. Themethod of claim 17, wherein, if a plurality of transformation unitsassociated with the coding unit are determined, the final quantizationparameter is determined differently with respect to different of theplurality of transformation units, respectively.